Network entities for supporting analytics generation

ABSTRACT

Analytics information can be used in a mobile network. Network entities and corresponding methods support the generation of such analytics information. In particular, network entities and methods can facilitate the gathering of information required for the analytics generation. A network entity for analytics generation may be configured to obtain network slice association (NSA) information and/or user plane association (UPA) information from one or more other network entities, where the NSA information indicates a relation between an Access Network (AN) property and a Core Network (CN) property, and the UPA information indicates a network entity configured to transmit data traffic to and/or from a user equipment in the network. Further, the network entity may be configured to provide analytics information, the analytics information being based on the obtained NSA information and/or UPA information.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of International Application No. PCT/EP2019/080557, filed on Nov. 7, 2019, the disclosure of which is hereby incorporated by reference in its entirety.

FIELD

The present disclosure relates to a new generation mobile network, and in particular to the generation of analytics information in the network. To this end, the disclosure proposes network entities and corresponding methods that support the analytics generation. In particular, the network entities and methods facilitate the gathering of information required for the analytics generation.

BACKGROUND

FIG. 1 illustrates an example of a mobile network based, which is on the 5G architecture, as per the 3GPP TS 23.501 specification. In particular, FIG. 1 shows the separation of the mobile network among: a management plane, a control plane, and user plane. Further, the separation of the mobile network among: an Access Network (AN), a Core Network (CN), and a Data Network (DN).

The mobile network operator can deploy and manage, via the management plane, different network slices. The management plane configures and manages the resources and entities associated with the network slice in both the ANs and the CNs. Each network slice will have associated to it control plane entities and user plane entities that are related, i.e., they belong to the same network slice. For simplicity, FIG. 1 illustrates only one network slice, which is identified by Single Network Slice Selection Assistance Information (S-NSSAI) #1, and illustrates the core plane and user plane entities associated with the network slice S-NSSAI#1. The control plane entities manage the connections of the User Equipments (UEs) at the user plane from N3 to the DN (including the control over the N9 connecting multiple User Plane Functions (UPFs)), while the user plane entities are the ones that actually transmit the data traffic related to the UEs and apply control actions/policies defined by the control plane entities.

The Network Data Analytics Function (NWDAF) is the network function in a 5G System (5GS), which is able to generate analytics information. In order to generate analytics information for specific UEs and/or specific groups of UEs, or Network Functions (NFs), or Applications, etc., the NWDAF needs to collect data from the NFs in the 5GS, or from external Application Functions (AFs), as well as from the Operation, Administration and Maintenance (OAM)/management plane. Examples of the data to be collected by the NWDAF are:

-   -   Location information of the UEs.     -   AN throughput per Tracking Area (TA), which is composed by a set         of cells, where the UE is located, and per network slice that         the UE is using in such TA.     -   User Plane Function (UPF) performance measurements associated         with UE sessions, collected from OAM.     -   Service data (e.g., Mean Opinion Scores (MOS)) from AFs,         collected via Network Exposure Function (NEF), if 3^(rd) Parry         AF, or directly from AF.

In 5GS Rel. 16, the NWDAF performs two different types of data collection:

-   -   Pre-data collection for determining the control plane NFs and/or         external AFs serving UEs (see 3GPP TS 23.288 Clause 6.2.2.1,         Table 6.2.2.1-2: NF Services consumed by NWDAF to determine,         which NF instances are serving a UE). In this case, the NWDAF         has to first:         -   Consume services of NFs, such as Unified Data Management             (UDM), Unified Data Repository (UDR), or Network Repository             Function (NRF), to determine the control plane NFs serving             the UEs, and thus in a second step to trigger the collection             of the actual data from the serving control plane NFs.     -   Raw data collection by:         -   Subscribing to events from NFs to collect raw data (e.g.,             events exposed by the Access and Mobility Management             Function (AMF) or Session Management Function (SMF).         -   Consuming services from OAM related to Performance             Management (PM) and/or Fault Management (FM) and/or             Provisioning Management, in order to collect the management             data.

The mechanisms defined in Rel. 16 for the pre-data collection are focused only on determining control plane NFs serving specific UEs that are used for the discovery of such NFs. However, the inventors have reconized that many issues were not yet addressed, in particular how the NWDA can perform pre-data collection without high load.

SUMMARY

In particular, the inventors realized that the following issues were not addressed:

-   -   1. Certain analytics idenfications (IDs) use specific         information on NFs and/or applications and/or network         measurements, and can be requested for an “area of interest”         (which defines a geographical region of a mobile network, e.g.,         in term of list of Tracking Area Identities (TAIs) and/or Cell         IDs in such geographical region), and not specifically related         to a certain UE(s).         -   For instance, there exist analytics IDs, which have as             filters for subscription a specific geographical area, such             as analytics IDs: Service Experience (3GPP TS 23.288 Clause             6.4) and User data congestion in a geographic area (3GPP TS             23.288 Clause 6.8.1).         -   In this case, the NWDAF has a mapping of the tuple “(TAs,             Cells ID, network slices, Network Slice Instances (NSIs)”,             in order to properly trigger the data collection in the             specific area of interest. However, there exists no             mechanism to determine, by the NWDAF, the association of             TAs, and/or Cell IDs, and/or S-NSSAIs, and/or NSIs during             the pre-data collection.     -   2. Certain analytics IDs generated by the NWDAF, such as Service         Experience (3GPP TS 23.288 Clause 6.4) require information to be         collected from UPFs. However, there exists no mechanism to         determine, by the NWDAF, the UPFs (and any other UP information)         that are serving UEs during the pre-data collection, such that         the NWDAF could request the data collection for such UPFs.

3GPP TS 23.288 V16.0.0 specifies in Clause 6.2.2.1 mechanisms that define the control plane NF services, which need to be consumed by the NWDAF, in order to determine which control plane NFs are serving UEs. However, there is so far no definition of a mechanism, in which the NWDAF determines mapping of core network and access network associated with an area of interest and/or in which the NWDAF determines user and/or control plane entities related to the data traffic to and/or from UEs.

According to the inventors' analysis, the current options for determining the association among TAs, cells, network slices, and NSIs, in an area of interest, with any of the existing mechanisms, are incomplete and/or would lead to a significant increase of the load for pre-data collection:

-   -   Option 1: NWDAF subscription to event Location Events from UDM         or AMF, as well as AMF Location information service (as defined         in 3GPP TS 23.502 V16.1.1).         -   UDM and AMF expose, via event exposure, information about UE             location, and the AMF offers the service to track UE             location, for instance, in terms of Cells, TA, Geodetic             Location as defined in TS 23.502 Clause 5.2.2.5. This             information exposed by UDM/AMF allows for the mapping of             individual and/or groups of UEs to Cells and/or TAs.             However, for the NWDAF to have the mapping of all Cell ID             mapped to TAs, the NWDAF must subscribe to all UDM/AMF to             consume the events of “any UE”. Therefore, the load of             pre-data collection is increased significantly. In addition,             the information is not complete, because the NWDAF would             still not have the information, which Cells, TA, are             associated with which network slices and/or NSIs, This             information is kept by UDM/AMF with the association             UE×S-NSSAI/NSI, and not clearly connected to UE×Cell×TA.     -   Option 2: NWDAF subscription to NRF status updates in NF         profiles.         -   Certain NF Profiles, such as AMF, SMF in NRF, contain the             list of TAIs they are associated with, as well as the list             of S-NSSAIs and NSIs associated with such NFs. Thus, the             NWDAF could subscribe to the NRF services to receive updates             in the NF profiles of such NF Types.         -   However, the NF Profile information is not complete,             because:             -   The TAI information does not contain any information of                 the Cells associated with the TAI (as described in 3GPP                 TS 29.571);             -   There is no direct association of which TAI is                 associated with each S-NSSAI and/or NSI.         -   In addition, this type of usage of the NRF services would             lead to an increase of the load of data collection, and             waste of resources, because:             -   For any update in an NF Profile (TS 23.502, Clause                 5.2.7.2.5), the NWDAF would be notified.             -   Updates on Load, or capacity (two NF profile parameters                 of any NF) can change dynamically over time, and can be                 used for the NF selection (e.g., TS 23.501 Clause 6.3.2                 and 6.3.5). For every change in any of these parameters                 of the NFs, the NWDAF subscribed at the NRF will receive                 a notification. However, as long as the TAI of such NFs                 did not change, such information is useless for the                 NWDAF.     -   Option 3: NWDAF subscription to NSSF service on NSSAI         availability, as defined in 3GPP TS 23.502 Clause 5.2.16.3.         -   The NWDAF can consume the NSSF services to obtain the             mapping on the availability of S-NSSAIs (i.e., allowed             network slices and/or NSIs) per TA.         -   However, this service still fails to provide the             information, which Cells are associated with which TAs. This             information is available to the NWDAF only by subscribing to             UE location events exposed by AMF, which means that the             NWDAF would need to subscribe to two different sources of             information to obtain the complete mapping of Cells×TAs.

Further, according to the inventors' analysis, the current limitations of the existing mechanisms for determining UP NFs serving UEs are:

-   -   Option 1: SMF does not expose events with any information about         UPFs, only about changes related to the DNN (TS 23.502 Clause         5.2.8.3.1), i.e., changes in the termination of interface N6         (which is the interface that connects the 5G mobile network to         the DNN/DNAI). Changes in interface N3 (connecting RAN to UPFs)         or interface N9 (UPFs to UPFs) are not exposed by SMF. The N3         and N9 changes are important for the NWDAF, because they define         the UPFs, which the NWDAF needs to collect raw data for the         generation of certain analytics IDs.     -   Option 2: In the NRF, the UPF Profile as well as the SMF Profile         have a list of strings that determine the “SMF Serving Area”         (3GPP TS 29.510). However, if more than one UPF is in the same         SMF serving area of one SMF instance, there is no way to         determine which UPF exactly is being used for sessions of UEs         (i.e., the data traffic of UEs).     -   Option 3: UDM or UDR datasets (as defined in 3GPP TS 23.502)         have only the SMF×UE×PDU ID mapping, and no information about         the UPFs is associated with the PDU ID.     -   Option 4: Another option could be OAM/Management Plane         provisioning services (3GPP TS 28.532) and resource models (3GPP         TS 28.541), which can expose the information of the SMFs         associated with the UPFs. However, the OAM cannot expose the         information in a finer granularity of SMFs×UPFs×UEs mapping.

In view of the above-mentioned options and their limitations, embodiments of the present disclosure aim to provide an improved mechanism for pre-data collection for generating analytics information.

Aspects of the present disclosure provide network entities and methods, which can support the analytics generation with an enhanced pre-data collection. In particular, all necessary information for the analytics generation are provided. Further, a load of the pre-data collection is significantly reduced. The pre-data collection may include the determination of user plane association (UPA) information and/or of network slice association (NSA) information. The term association information is also used to denote “user plane association (UPA) information and/or of network slice association (NSA) information”.

A first aspect of the disclosure provides a network entity for analytics generation, the network entity being configured to: obtain NSA information and/or UPA information from one or more other network entities; wherein the NSA information indicates a relation between an AN property and a CN property, and the UPA information indicates a network entity configured to transmit data traffic to and/or from a user equipment in the network, and provide analytics information, the analytics information being based on the obtained NSA information and/or UPA information.

The network entity of the first aspect can acquire the NSA information and/or UPA information that is necessary for generating the analytics information. In particular, the network entity can obtain this association information with reduced signalling, and thus with reduced load. Accordingly, the network entity supports enhanced pre-data collection for the analytics generation.

In an implementation form of the first aspect, the network entity is further configured to: obtain the NSA information and/or UPA information by configuration from a management plane entity.

This is a simple and direct way for the network entity to obtain the NSA information and/or UPA information. For instance, the network entity may be configured by OAM.

In an implementation form of the first aspect, the network entity is further configured to: send a request and/or subscribe to one or more NFs; and obtain the NSA information and/or UPA information from the one or more NFs, in response to the request and/or according to the subscription.

The network entity can directly consume the association information necessary for generating the analytics information from the one or more NFs. The network entity may be configured to contact different types of NFs for the association information. The network entity has thus great flexibility to obtain the necessary information, while keeping the network load low.

In an implementation form of the first aspect, the request and/or the subscription respectively comprises a request and/or subscription for NSA and/or UPA information.

In an implementation form of the first aspect, the network entity is further configured to: send a plurality of requests and/or subscribe to a plurality of NFs; obtain the NSA information and/or UPA information from the plurality of NFs, in response to the plurality of requests and/or according to the subscriptions; aggregate the obtained NSA information and/or UPA information; and provide the analytics information, the analytics information being based on the aggregated NSA information and/or UPA information.

In an implementation form of the first aspect, the network entity is further configured to: send a request and/or subscribe to a determined NF; obtain the NSA information and/or UPA information from the determined NF, in response to the request and/or according to the subscription; and provide the analytics information, the analytics information being based on the obtained NSA information and/or UPA information.

The network entity can thus obtain the necessary information for generating the analytics information from one dedicated NF, also referred to as intermediary NF or the determined NF, since it may gather that information from other NFs. For the network entity of the first aspect, this is a very efficient option to obtain the association information it needs.

In an implementation form of the first aspect, the network entity is a control plane entity, in particular comprising a NWDAF.

A second aspect of the disclosure provides a network entity for supporting analytics generation, the network entity being configured to: provide NSA information and/or UPA information to another network entity, in response to a request received from and/or according to a subscription from the other network entity; wherein the NSA information indicates a relation between an AN property and a CN property, and the UPA information indicates a network entity configured to transmit data traffic to and/or from a user equipment in the network, and/or provide NSA information and/or UPA information to another network entity, upon changes in one or more target elements related to the NSA information and/or UPA information. The one or more target elements are related to the other network entity.

The network entity of the second aspect supports the analytic generation by providing the NSA and/or UPA information, for instance, to the network entity of the first aspect. In particular, the network entity of the second aspect supports pre-data collection for analytics generation with information that is, of today, not available to analytics generation.

In an implementation form of the second aspect, the network entity is a control plane NF, in particular comprising a SMF, and/or an AMF and/or a Network Slice Selection Function (NSSF) and/or NEF and/or AF and/or Network Repository Function (NRF).

A third aspect of the disclosure provides a network entity for supporting analytics generation, the network entity being configured to: obtain NSA information and/or UPA information from another network entity, in response to a first request sent to and/or according to a first subscription to the other network entity; wherein the NSA information indicates a relation between an AN property and a CN property, and the UPA information indicates a network entity configured to transmit data traffic to and/or from a user equipment in the network; and/or obtain NSA information and/or UPA information from another network entity, upon changes in one or more target elements related to the NSA information and/or UPA information. The one or more target elements are related to the other network entity.

The network entity of the third aspect supports the analytic generation by gathering and maintaining the NSA and/or UPA information. It can then provide the necessary association information for generating analytics information, for instance, to the network entity of the first aspect. In particular, the network entity of the third aspect supports pre-data collection for the analytics generation with both new information that was not previously available to analytics generation with significantly reduced load. The significantly reduced load can be particularly achieved when the network entity of the third aspect obtains association information upon changes in one or more target elements related to the NSA information and/or UPA information. This implicitly means that existing communications between the network entity of the third aspect and the other network entities can be enhanced, reused, piggybacked to include association information, therefore eliminating the need for extra signalling in the systems for the gathering of association information.

In an implementation form of the third aspect, the network entity is further configured to: obtain a second request and/or a second subscription, for NSA information and/or UPA information, from a further network entity; and provide the obtained NSA information and/or UPA information and/or aggregated NSA information and/or UPA information to the further network entity, in response to the second request and/or according to the second subscription.

Accordingly, the network entity of the third aspect can thus provide the NSA information and/or UPA information, which it collected from one or more other network entities (e.g., NFs) to the further network entity (e.g., the network entity of the first aspect). The network entity of the third aspect can thus act as intermediary network entity (e.g., intermediary NF, or determined NF) between the network entity of the first aspect and other network entities (e.g., other NFs).

In an implementation form of the third aspect, the network entity is further configured to: aggregate the obtained NSA information and/or UPA information, and/or store the obtained NSA information and/or UPA information.

Thus, the network entity generating the analytics information can perform the generation more efficiently and faster based on the already pre-processed NSA and/or UPA information.

In an implementation form of the third aspect, the network entity is a control plane entity, in particular comprising a Unified Data Management (UDM) and/or Unified Data Repository (UDR) and/or NWDAF.

A fourth aspect of the disclosure provides a network entity, in particular a management plane entity, for supporting analytics generation, the network entity being configured to: configure another network entity with NSA information and/or UPA information, wherein the other network entity is, in particular, a NWDAF, and/or a UDM and/or a UDR, and wherein the NSA information indicates a relation between an AN property and a CN property, and the UPA information indicates a network entity configured to transmit data traffic to and/or from a user equipment in the network.

The network entity of the fourth aspect supports the analytic generation by configuring the necessary association information at the responsible network entity. It can configured the necessary association information for generating analytics information, for instance, at the network entity of the first aspect. In particular, the network entity of the fourth aspect supports pre-data collection for the analytics generation with significantly reduced load. In particular for the case of network slice association information, where no control plane signalling is required for the network entity being configured, for instance the network entity of the first aspect, to obtain the NSA information.

In an implementation form of any of the first aspect to fourth aspect or any implementation form thereof, the NSA information comprises at least one of: a cell related to a TA, Access Type, and/or one or more allowed S-NSSAIs and/or allowed NSI(s) and/or one or more restricted S-NSSAIs and/or restricted NSI(s) and/or one or more NFs, one or more allowed S-NSSAI(s) and/or allowed NSI(s) per public land mobile network (PLMN) for each related NF; a cell related to a TA, Access Type, and/or one or more allowed S-NSSAIs and/or allowed NSI(s) and/or one or more restricted S-NSSAIs and/or restricted NSI(s) and/or one or more NFs, one or more restricted S-NSSAI(s) and/or restricted NSI(s) per PLMN for each related NF; a TA related to a list of Cells, a supported Access Type, and/or one or more allowed S-NSSAI(s) and/or allowed NSI(s), and/or one or more NFs, one or more allowed S-NSSAI(s) and/or allowed NSI(s) for each related NF; a TA related to a list of Cells, a supported Access Type, and/or one or more restricted S-NSSAI(s) and/or restricted NSI(s) per PLMN, and/or one or more NFs, one or more restricted S-NSSAI(s) and/or restricted NSI(s) per PLMN for each related NF; a NF related to a TA(s), for the TA, one or more related Cells, one or more related Access Types, one or more related allowed S-NSSAI(s) and/or allowed NSI(s); a NF related to a TA(s), for the TA, one or more related Cells, one or more related Access Types, one or more related restricted S-NSSAI(s) and/or restricted NSI(s) per PLMN.

In an implementation form of any of the first aspect to fourth aspect or any implementation form thereof, the network entity is further configured to, wherein the UPA information comprises at least one of: one or more user plane NFs transmitting Uplink, UL, and/or Downlink, DL, data traffic related to one or more User Equipments, UEs, and/or one or more groups of UEs, and/or one or more and/or UE session, and/or one or more data network identification (e.g., DNN or DNAI), and/or one or more network slice identification (e.g., S-NSSAI and/or NSI, and/or NSSAI), and/or one or more application identification (e.g., AF identifier); one or more control plane NFs transmitting UL and/or DL data traffic related to one or more UEs and/or one or more groups of UEs and/or one or more UE sessions, and/or one or more data network identification (e.g., DNN or DNAI), and/or one or more network slice identification (e.g., S-NSSAI and/or NSI, and/or NSSAI), and/or one or more application identification (e.g., AF identifier); one or more user plane interfaces, and/or links, and/or reference points, and/or services, transmitting UL and/or DL data traffic related to one or more UEs and/or one or more groups of UEs and/or one or more UE sessions, and/or one or more data network identification (e.g., DNN or DNAI), and/or one or more network slice identification (e.g., S-NSSAI and/or NSI, and/or NSSAI), and/or one or more application identification (e.g., AF identifier); one or more control plane interfaces, and/or links, and/or reference points, and/or services, transmitting UL and/or DL data traffic related to one or more UEs and/or one or more groups of UEs and/or one or more UE sessions, and/or one or more data network identification (e.g., DNN or DNAI), and/or one or more network slice identification (e.g., S-NSSAI and/or NSI, and/or NSSAI), and/or one or more application identification (e.g., AF identifier).

A fifth aspect of the disclosure provides a method for analytics generation, the method comprising: obtaining NSA information and/or UPA information from one or more network entities; wherein the NSA information indicates a relation between an AN property and a CN property, and the UPA information indicates a network entity configured to transmit data traffic to and/or from a user equipment in the network; and provide analytics information, the analytics information being based on the obtained NSA information and/or UPA information.

The method of the fifth aspect can have implementation forms that correspond to the implementation forms of the network entity of the first aspect. Accordingly, the method of the fifth aspect and its possible implementation forms achieve the same advantages and effects as the network entity of the first aspect and its respective implementation forms.

A sixth aspect of the disclosure provides a method for supporting analytics generation, wherein the method can be performed by a network entity, the method comprising: providing NSA information and/or UPA information to another network entity, in response to a request received from and/or according to a subscription from the other network entity; wherein the NSA information indicates a relation between an AN property and a CN property, and the UPA information indicates a network entity configured to transmit data traffic to and/or from a user equipment in the network and/or providing NSA information and/or UPA information to another network entity, upon changes in one or more target elements related to the NSA information and/or UPA information, wherein the one more target elements may be related to the network entity performing the method.

The method of the sixth aspect can have implementation forms that correspond to the implementation forms of the network entity of the second aspect. Accordingly, the method of the sixth aspect and its possible implementation forms achieve the same advantages and effects as the network entity of the second aspect and its respective implementation forms.

A seventh aspect of the disclosure provides a method for supporting analytics generation, the method comprising: obtaining NSA information and/or UPA information from another network entity, in response to a first request sent to and/or according to a first subscription to the other network entity; wherein the NSA information indicates a relation between an AN property and a CN property, and the UPA information indicates a network entity configured to transmit data traffic to and/or from a user equipment in the network, and/or obtaining NSA information and/or UPA information from another network entity, upon changes in one or more target elements related to the NSA information and/or UPA information.

The method of the seventh aspect can have implementation forms that correspond to the implementation forms of the network entity of the third aspect. Accordingly, the method of the seventh aspect and its possible implementation forms achieve the same advantages and effects as the network entity of the third aspect and its respective implementation forms.

An eighth aspect of the disclosure provides a method for supporting analytics generation, the method comprising: configuring a network entity with NSA information and/or UPA information, wherein the other network entity is, in particular, a NWDAF and/or a UDM and/or a UDR, and wherein the NSA information indicates a relation between an AN property and a CN property, and the UPA information indicates a network entity configured to transmit data traffic to and/or from a user equipment in the network.

The method of the eighth aspect can have implementation forms that correspond to the implementation forms of the network entity of the fourth aspect. Accordingly, the method of the eighth aspect and its possible implementation forms achieve the same advantages and effects as the network entity of the fourth aspect and its respective implementation forms.

A ninth aspect of the disclosure provides a computer program comprising a program code for performing the method according to the fifth, sixth, seventh or eighths aspect, when executed on a computer.

DEFINITIONS

In the following, some terms used in this document are generally defined.

Analytics Function: may be a NF that receives a request and/or subscription to analytics information from a consumer, and can perform analytics information generation. An example of an Analytics Function is the NWDAF (Network Data Analytics Function) of 3GPP 5G Architecture defined in TS 23.501. The Analytics function may be implemented by the network entity of the first aspect.

Analytics Information: is the output of an Analytics Functions, for instance an Analytics ID, as defined in 3GPP TS 23.288, such as the analytics IDs listed in Clauses 6.4-6.9 in TS 23.288 V16.1.0.

Analytics Information Generation: is a process, in which the Analytics Function may trigger raw data collection (if data is not available) and/or selects previously collected raw data (raw data being, for instance, throughput of a Cell, bitrate of PDU session ID in an UPF)) and use such raw data to perform calculations and/or applies statistical analysis, and/or applies ML/AI techniques (such as regression models, neural networks, etc.) to produce an output, i.e., generate the analytics information.

User Plane Association (UPA) information: defines the 5GS entities configured to transmit data traffic to and/or from UE(s) in the mobile network, i.e., UE communication. The UPA information can also be defined as a mapping among one or more CN properties (e.g., UE identification, NF instance identification, N3/N6/N9 interfaces identification, DNN identification, network slice identification, PDU session identification, type of UE traffic—i.e., UP based or CP) and the transmitted data traffic to and/or from UEs. Some examples of possible UE communications are listed below:

-   -   If the UE communication is defined as a session between a UE and         DN, the 5GS entities and their properties in the user plane that         are used for such UE communication may be: UE, Cell(s), N3(s),         UPF(s), N9 if more than one UPF is used, N6(s), and DNN/DNAI, as         described in the overall architecture of 3GPP TS 23.501.     -   If the UE communication is defined as Non-IP Data Delivery, then         the 5GS entities that can be used for such UE communication may         be: Cell, NEF, SMF, AF (as defined in 3GPP TS 23.501 and TS         23.502).     -   If the UE communication is, for instance, Vehicle-to-Anything         (V2X), the user plane entities that are used for such UE         communication could be: UE, Cell, Road Side Unit (RSU), UPF,         etc.

The UPA information may comprise at least one of:

-   -   One or more “user plane NFs” transmitting UL and/or DL data         traffic related to one or more UE(s) and/or groups of UE, and/or         one or more UE session identification, and/or one or more data         network identification (e.g., DNN or DNAI), and/or one or more         network slice identification (e.g., S-NSSAI and/or NSI, and/or         NSSAI), and/or one or more application identification (e.g., AF         identifier).     -   One or more “core plane NFs” transmitting UL and/or DL data         traffic related to one or more UE(s) and/or groups of UE ,         and/or one or more UE session identification, and/or one or more         data network identification (e.g., DNN or DNAI), and/or one or         more network slice identification (e.g., S-NSSAI and/or NSI,         and/or NSSAI), and/or one or more application identification         (e.g., AF identifier).     -   One or more “user plane interfaces and/or links and/or reference         points and/or services” transmitting UL and/or DL data traffic         related to one or more UE(s) and/or groups of UE, and/or one or         more UE session identification, and/or one or more data network         identification (e.g., DNN or DNAI), and/or one or more network         slice identification (e.g., S-NSSAI and/or NSI, and/or NSSAI),         and/or one or more application identification (e.g., AF         identifier).     -   One or more “core plane interfaces and/or links and/or reference         points and/or services” transmitting UL and/or DL data traffic         related to one or more UE(s) and/or groups of UE, and/or one or         more UE session identification, and/or one or more data network         identification (e.g., DNN or DNAI), and/or one or more network         slice identification (e.g., S-NSSAI and/or NSI, and/or NSSAI),         and/or one or more application identification (e.g., AF         identifier).

Network Slice Association (NSA) information: may define the mapping among an AN property (e.g., respectively, cells ID, tracking area/access type) and a CN property (e.g., respectively, NFs ID, Interfaces ID, allowed or restricted S-NSSAIs/NSIs) for a network slice (e.g., S-NSSAI) and/or a NSI).

The NSA information may comprises at least one of:

-   -   A cell related to a TA, Access Type, and/or one or more allowed         S-NSSAIs and/or allowed NSI(s) and/or one or more restricted         S-NSSAIs and/or restricted NSI(s) and/or one or more NFs, one or         more allowed S-NSSAI(s) and/or allowed NSI(s) per PLMN for each         related NF     -   A cell related to a TA, Access Type, and/or one or more allowed         S-NSSAIs and/or allowed NSI(s) and/or one or more restricted         S-NSSAIs and/or restricted NSI(s) and/or one or more NFs, one or         more restricted S-NS SAI(s) and/or restricted NSI(s) per PLMN         for each related NF     -   a TA related to a list of Cells, a supported Access Type, and/or         one or more allowed S-NSSAI(s) and/or allowed NSI(s), and/or one         or more NFs, one or more allowed S-NSSAI(s) and/or allowed         NSI(s) for each related NF     -   a TA related to a list of Cells, a supported Access Type, and/or         one or more restricted S-NSSAI(s) and/or restricted NSI(s) per         PLMN, and/or one or more NFs, one or more restricted S-NSSAI(s)         and/or restricted NSI(s) per PLMN for each related NF     -   a NF related to a TA(s), for the TA, one or more related Cells,         one or more related Access Types, one or more related allowed         S-NSSAI(s) and/or allowed NSI(s)     -   a NF related to a TA(s), for the TA, one or more related Cells,         one or more related Access Types, one or more related restricted         S-NSSAI(s) and/or restricted NSI(s) per PLMN

Association information: is equivalent of using the term “NSA information and/or UPA information”.

Target element related to UPA information: may be UEs and/or group of UEs, and/or PDU session, and/or, data network identification, and/or network slice identification.

Target element related to NAS information: may be TA(s) and/or Cell(s) identification, and/or Access Types and/or, network slice identification, a NF related to a TA(s), and/or network slice identification related to TA.

NF that detects, generates association information: may be an NF that has the ownership of the NSA information and/or UPA information. For instance, an NF that detects UPA information, is the one that can define the set of UPFs and UP interfaces that will be used for the establishment of UE sessions in the mobile network, such as SMF in 5GS. An example for a NF that generates NSA information is the AMF, which has the control of which cell is associated with which TA, and which network slices (i.e., S-NSSAI) and/or NSIs are allowed in a TA.

NF enhanced with association information: may be a NF that detects and/or generates association information and exposes such association information, i.e., provides ways to other network entities in the system to obtain such information. The association information exposed by such a NF may be an individual basis, for instance, the association information may be detected by a specific NF type and instance (or NF set) that qualifies the NF enhanced with association information (e.g., NF Type SMF, NF type AMF, NF Type SMF set A, etc.). This NF enhanced with association information may be implemented by the network entity of the second aspect.

NF enhanced with centralization of association information (i.e., the determined NF): may be a NF capable of obtaining (e.g., invoking services), e.g., from one or more NF enhanced with association information from the same NF Type and/or NF set, the association information, storing and/or aggregating (and storing) such association information, and being able to provide queries and/or search/ and/or retrieval of the association information to other entities in the network. Examples of information that can be exposed by the NF enhanced with centralization of association information may be not in individual basis, i.e., for instance the association information that can be provided is related to different types of NFs and/or NF sets. This NF enhanced with centralization of association information may be implemented by the network entity of the third aspect.

It is possible that a same network entity can perform the role of a NF enhanced with association information as well as a NF enhanced with centralized association information. In this case, there would exist only one visible service between such NF with both roles and the Analytics Function. That is, the network entity of the second aspect may also be the network entity of the third aspect.

It is possible that an Analytics Function performs also the role of a NF enhanced with centralization of association information. In this case, the interactions between NF with enhanced association information and Analytics Function would be visible to 5GS. That is, the network entity of the first aspect may be the network entity of the third aspect.

Generating analytics information based on association information: The Analytics Function generating analytics information, may require data (i.e., raw data such throughput of a Cell). Nevertheless, the collection of raw data to be used for analytics generation may depend on the target of the analytics information. For instance, one analytics information should be provided for a group of UEs #1, or a set of NFs {a,b,c}. Therefore, before triggering the data collection or using the collected data, the Analytics Function may need, in a first moment, to determine which NF instances are serving a UE (which are the target of the analytics information), as well as AN and network slices and/or network slice instances (which are the target of the analytics information), and in a second step trigger the collection of data and/or use already collected data from the serving NFs and or Cells and/or network slices and/or network slices instances. The Analytics Function thus, may use the association information as filter to determine/select which entities to trigger the raw data collection and/or as filter to select subsets of already raw collected data.

Discovering of proper association information provider: The Analytics Function may acquire the information, such as address and/or ID, of the NF that can provide the association information. For instance, acquiring could be based on checking configurations that map UEs to NFs, or interacting with discovery repositories (such as NRF in 5GS) to acquire the address of the NF serving the UEs.

It has to be noted that all devices, elements, units and means described in the present disclosure could be implemented in the software or hardware elements or any kind of combination thereof. All steps which are performed by the various entities described in the present disclosure as well as the functionalities described to be performed by the various entities are intended to mean that the respective entity is adapted to or configured to perform the respective steps and functionalities. Even if, in the following description of exemplary embodiments, a specific functionality or step to be performed by external entities is not reflected in the description of a specific detailed element of that entity which performs that specific step or functionality, it should be clear for a skilled person that these methods and functionalities can be implemented in respective software or hardware elements, or any kind of combination thereof.

BRIEF DESCRIPTION OF DRAWINGS

The above described aspects and implementation forms of the present disclosure will be explained in the following description of exemplary embodiments in relation to the enclosed drawings, in which:

FIG. 1 shows an example of a mobile network following a 5G architecture as defined by 3GPP.

FIG. 2 shows a network entity for analytics generation, according to an embodiment of the disclosure.

FIG. 3 shows a network entity for supporting analytics generation, according to an embodiment of the disclosure.

FIG. 4 shows a network entity for supporting analytics generation, according to an embodiment of the disclosure.

FIG. 5 shows a network entity for supporting analytics generation, according to an embodiment of the disclosure.

FIG. 6 shows various network entities, according to embodiments of the disclosure, implementing different operation modes 1-3.

FIG. 7 shows an example embodiment of operation mode 1.

FIG. 8 shows an example embodiment of operation mode 2.

FIG. 9 shows an example embodiment of operation mode 3.

FIG. 10 shows a method for analytics generation, according to an embodiment of the disclosure.

FIG. 11 shows different methods, according to embodiments of the disclosure, for supporting analytics generation.

DETAILED DESCRIPTION

FIG. 2 shows a network entity 200 according to an embodiment of the disclosure. The network entity 200 is configured to generate analytics. The network entity 200 may be a control plane entity, in particular, it may be or comprise a NWDAF. The network entity 200 may implement an Analytics Function.

The network entity 200 is configured to obtain NSA information 201 and/or UPA information 202 from one or more other network entities 210. The one or more other network entities may comprise a network entity 310 (see FIG. 3), which may be a control plane NF, in particular comprising a SMF and/or AMF and/or an NSSF and/or a NEF and/or an AF and/or a NRF. The one or more other network entities may also comprise a determined network entity 410 (see FIG. 4), which may be a control plane entity, in particular comprising a UDM and/or UDR and/or NWDAF. The one or more other network entities may also comprise a network entity 510 (see FIG. 5), which may be a management plane entity.

The network entity 200 is further configured to provide analytics information 203, wherein the analytics information 203 is based on the obtained NSA information 201 and/or UPA information 202. That is, it may generate the analytics information based on the association information 201/202. The network entity 200 may also expose and/or send the analytic information 203 and/or the association information 201/202 to another network entity.

FIG. 3 shows a network entity 310 according to an embodiment of the disclosure. The network entity 310 is configured to support analytics generation, for instance, as performed by the network entity 200 of FIG. 2 and/or by a NWDAF. The network entity 310 may be a control plane NF, in particular comprising a SMF and/or AMF and/or an NSSF and/or a NEF and/or an AF and/or a NRF.

The network entity 310 is configured to provide NSA information 201 and/or UPA information 202 to another network entity 300, in response to a request 301 received from and/or according to a subscription from the other network entity 300. Alternatively, or in addition, the network entity 310 may be configured to provide NSA information 201 and/or UPA information 202 to another network entity 300, upon changes in one or more target elements related to the NSA information 201 and/or UPA information 202. The one or more target elements being related to the network entity 310.

The other network entity 300 may be the network entity 200 shown in FIG. 2, i.e., may be a network entity according to an embodiment of the disclosure. Accordingly, the other network entity 300 may be, or comprise, a NWDAF and/or may implement an Analytics Function.

FIG. 4 shows a network entity 410 according to an embodiment of the disclosure. The network entity 410 is configured to support analytics generation, for instance, as performed by the network entity 200 of FIG. 2 and/or by a NWDAF. The network entity 410 may be a control plane entity, in particular comprising a UDM and/or UDR and/or NWDAF.

The network entity 410 is configured to obtain NSA information 201 a and/or UPA information 202 a from another network entity 420, in response to a first request 411 sent to and/or according to a first subscription to the other network entity 420. Alternatively, or in addition, the network entity 410 is configured to obtain NSA information 201 b and/or UPA information 202 b from another network entity 420, upon changes in one or more target elements related to the NSA information 201 b and/or UPA information 202 b. The one or more target elements being related to the other network entity 420.

The other network entity 420 may be may be a control plane NF, in particular comprising a SMF and/or AMF and/or an NSSF and/or a NEF and/or an AF and/or a NRF.

The network entity 410 may be further configured to (indicated in FIG. 4 as being optional by the dotted lines) to obtain a second request 401 and/or a second subscription, for NSA information 201 and/or UPA information 202, from a further network entity 400, and to provide the obtained NSA information 201 a, 201 b and/or UPA information 202 a, 202 b and/or aggregated NSA information 201 a, 201 b and/or UPA information 202 a, 202 b to the further network entity 400, in response to the second request 401 and/or according to the second subscription.

The further network entity 400 may be the network entity 200 shown in FIG. 2, i.e., it may be a network entity according to an embodiment of the disclosure. Accordingly, the further network entity 400 may be, or comprise, a NWDAF and/or may implement an Analytics Function.

FIG. 5 shows a network entity 510 according to an embodiment of the disclosure. The network entity 510 is configured to support analytics generation, for instance, as performed by the network entity 200 of FIG. 2 and/or by a NWDAF. The network entity 510 may be a management plane entity, e.g. OAM.

The network entity 510 is configured to configure another network entity 500 with NSA information 201 and/or UPA information 202.

The other network entity 500 is, in particular, a NWDAF, and/or a UDM, and/or a UDR. The other network entity 500 may be the network entity 200 shown in FIG. 2, i.e., it may be a network entity according to an embodiment of the disclosure.

In particular, the network entity 200 of FIG. 2 may be an NWDAF and may obtain the NSA information 201 and/or the UPA information 202 from the network entity 310 being an SMF/AMF; and/or may obtain the NSA information 201 and/or UPA information 202 from the determined network entity 410 being an UDM/UDR; and/or may be configured by the network entity 510 being an OAM with the NSA information 201 and/or UPA information 202.

Each network entity shown in FIG. 2-FIG. 5 may comprise processing circuitry configured to perform, conduct or initiate the various operations of the network entity described herein. The processing circuitry may comprise hardware and/or software. The hardware may comprise analog circuitry or digital circuitry, or both analog and digital circuitry. The digital circuitry may comprise components such as application-specific integrated circuits (ASICs), field-programmable arrays (FPGAs), digital signal processors (DSPs), or multi-purpose processors. In one embodiment, the processing circuitry comprises one or more processors and a non-transitory memory connected to the one or more processors. The non-transitory memory may carry executable program code which, when executed by the one or more processors, causes the network entity to perform, conduct or initiate the operations or methods described herein.

The main advantages of providing network entities as shown in FIG. 2-FIG. 5 are:

-   -   Enables the collection of the association information 201/202         for the generation of analytics information 203, such as the         ones defined in TS 23.288 not only for UP data traffic for         UE-DNN/DNAI communication, but allows also the determination of         entities (CP and UP) serving UEs in other kind of UE data         traffic communication (such as NIDD).     -   Reduces signaling generated by the network entity 200         responsible for the analytics generation (e.g. the NWDAF), for         determining the mapping of Cells, TAs, NFs, S-NSSAIs, NSIs,         because the network entity 200 does not need to consume         information from different sources (e.g., different service         operations even for the same NF) to identify the NSA information         201 and/or UPA information 202 for triggering the raw data         collection for the analytics information 203 generation.     -   Clearly differentiates the role among the different network         entities, e.g. the NWDAF, UDM, NRF, respectively, when it comes         to managing the NSA information 201 and/or UPA information 202         between the UEs and network slice entities and internal network         slice entities/configuration. The network entity 200 (e.g. the         NWDAF) does not have to assume the same role as, e.g., the UDM         on tracking the NFs serving the UEs, nor as the NRF role of         tracking association of Network Slice entities.

FIG. 6 shows different operation modes that can be implemented based on the network entities described with respect to FIG. 2-FIG. 5. In particular, three operation modes 1, 2 and 3 are envisaged. Further, the network entity 200 of FIG. 2, the network entity 310 of FIG. 3, and the network entity 410 of FIG. 4 are considered in FIG. 6.

Operation Mode 1 (Configuration Based): In this operation mode 1, the network entity 200 (here Analytics Function; e.g. the NWDAF) is configured by a management (network) entity 510 (see FIG. 5) with the NSA information 201 and/or UPA information 202. Alternatives for performing the configuration are:

-   -   The management entity 510 may directly change the configuration         of the NSA information 201 and/or UPA information stored in the         Analytics Function 200. For instance, the management entity 510         may have the definition in a data structure of the Analytics         Function 200, and this data structure may be enhanced with the         association information 201/202. Therefore, when the Analytics         Function 200 is deployed in the mobile network, the management         entity 510 may configure (and update if changes happen) such         data structure with the proper association information 201/202.     -   The Analytics Function 200 may provide a service and/or an         interface so that the management entity 510 may invoke/access         such service and/or interface, and may provide (e.g., by sending         as input parameters of a service operation) the NSA information         201 and/or UPA information 202.

The steps in the operation mode 1 may be:

-   -   1. The management entity 510 configures the Analytics Function         200 with the NSA information 201 and/or UPA information 202.     -   2. The Analytics Function 200 generates the analytics         information 203 based on the NSA information 201 and/or UPA         information 202.

Operation Mode 2 (Distributed collection of association information): In this operation mode 2, the network entity 200 (here Analytics Function; e.g. the NWDAF) may directly consume the NSA information 201 and/or UPA information 202 from one or more NFs 310 enhanced with association information (see FIG. 3). The Analytics Function 200 may need to contact different types of NFs 310 (e.g., SMF, AMF, NSSF, etc.), in order to collect the NSA information 201 and/or UPA information 202. Different options, how the NFs 310 enhanced with association information may expose the NSA information 201 and/or UPA information 202, are discussed below.

The steps in operation mode 2 may be:

(a) The Analytics Function 200 may request and/or subscribe to the NFs 310 enhanced with association information for the NSA information 201 and/or UPA information 202. (b) The NFs 310 enhanced with association information may send, notify (eventually periodically) the requested the NSA information 201 and/or UPA information 202. Examples of alternatives of how the Analytics Function 200 can consume (i.e., obtain) the association information 201/202 from the NF 310 enhanced with association information are listed below:

-   -   Following the Network exposure model defined in 3GPP TS 23.501:         where a NF 310 enhanced with association information has its         list of exposed events extended to include events for         association; as well as, if required, extensions to the         appropriate service operations to allow other entities to         consume such service and therefore the UP and/or network slice         association events.     -   Providing new dedicated service operations to allow consumers to         request and/or subscribe to the association information 201/202         the NF 310 provides.     -   1. (a) Optionally, the Analytics Function 200 can perform some         processing (e.g., aggregation) of the NSA information 201 and/or         UPA information 202 obtained from different NFs 310 enhanced         with association information, before storing and/or using such         association information 201/202. (b) The Analytics Function 200         may generate the analytics information 203 based on the         aggregated and/or obtained NSA information 201 and/or UPA         information 202.

Operation Mode 3 (Centralized collection of association information): In this operation mode 3, the network entity 200 (here Analytics Function; e.g. the NWDAF) may consume the NSA information 201 and/or UPA information 202 from a NF 410 enhanced with centralization of association information (e.g., the determined NF) (see FIG. 4).

The steps in operation mode 3 may be:

-   -   1. In this step, there exist an intermediary NF 410 enhanced         with centralization of association information (e.g., the         determined NF), which obtains the NSA information 201 and/or UPA         information 202. Different options can be applied for this, such         as the ones below:         -   1a. (Option 1: Configuration centric): The management entity             510 may configure the NF 410 enhanced with centralization of             association information. The same alternatives for             performing the configuration described in operation mode 1             apply in this case, but now instead of the Analytics             Functions 200, the configured entity is the NF 410 enhanced             with centralization of association information.         -   1b-c. (Option 2: Detecting NF centric): The intermediary NF             410 enhanced with centralization of association information             may request and/or subscribe to the NF 310 enhanced with             association information (see FIG. 3) for the NSA information             201 and/or UPA information 202, and may receive the             requested association information 201 a/202 a (eventually             periodically in the case of subscription/notify). The same             alternatives discussed in operation mode 2 for             consuming/obtaining association information 201 a/202 a from             the NF 310 may apply in this case.         -   1d. (Option 3: Intermediary NF centric): The NF 310 enhanced             with association information may provide the NSA information             201 b and/or UPA information 202 b to the intermediary NF             410 enhanced with centralization of association information             upon changes in target elements of association information,             the one or more target elements being related to the NF 310             enhanced with association information.. For instance, one             possible alternative for the NF 310 enhanced with             association to provide such information is by using             interfaces and/or service operations from the intermediary             NF 410 enhanced with centralization of association             information. An example of changes in UPA information 202 is             the session of an UE (e.g., the one target element of UPA             information) is rerouted to a different UPF, and this means             that the UP association information related to such target             element changed. An example of a change in the NSA             information 201 is the inclusion of a new Cell in a TA of an             S-NSSAI, this means that the target element (e.g., the TA)             of the network slice association information has changed.     -   2. (a) Optionally, the intermediary NF 410 enhanced with         centralization of association information can perform some         processing (e.g., aggregation) of the association information         201 a/201 b/202 a/202 b obtained from the different NFs 310         enhanced with association information, before storing and/or         using such association information. (b) The intermediary NF 410         enhanced with centralization of association information can also         stores the obtained and/or aggregated NSA information 201 and/or         UPA information 202.     -   3. (a-b) The Analytics Function 200 may request and/or subscribe         and/or search for association information 201/202 from the         intermediary NF 410 enhanced with centralization, and may         receive the required associated information 201/202.     -   4. The Analytics Function 200 may generate the analytics         information 203 based on association information 201/202.

The following details are common to all operation modes 1-3:

Possible examples of processing (e.g., aggregation) that can be executed over the association information 201/202, for instance, either by the Analytics Function 200 and/or by the intermediary NF 410 enhanced with centralization of association information, are:

-   -   When the association information 201/202 obtained by the network         entity (i.e., Analytics Function 200 and/or intermediary NF 410         enhanced with centralization of association information) is         provided by a another entity (e.g., NF 310 enhanced with         association information) that has a dedicated service and/or         provides a specific data structure that organize the association         information (i.e., NSA and/or UPA information 201/202), then the         aggregation may just include adding, concatenating, grouping the         obtained association information 201/202 according with the         dataset key (e.g., database key for a dataset) used by the         network entity to organize the association information 201/202.         Examples of dataset key are: S-NSSAI and/or TA for NSA         information, while for UPA an example is the UE identification         (such as SUPI).     -   When the association information 201/202 obtained by the network         entity (i.e., Analytics Function 200 and/or intermediary NF 410         enhanced with centralization of association information) is         provided by another entity (e.g., NF 310 enhanced with         association information) that does not have a dedicated service         to provide the association information 201/202 and/or a data         structure that directly reflects the association information         201/202 (i.e., the parameters of the service operation are not a         direct mapping to the fields of the data structure of the         association information), the association information 201/202         can be mixed with other type of information (e.g., UE context         managed for instance by AMF and/or SMF network functions in 5GS,         wherein inside the UE context it is possible to extract some NSA         information such as Cell ID×TA×Access Technology from the         overall data structure of UE context). In this case, when the         network entity 200/410 may obtain the information from the other         entity 310, the network entity 200/410 may first need to process         such received information, and extract the association         information 201/202 from the overall received information. Thus,         the aggregation executed by the network entity 200/410 may         comprise a sequence of processing steps. Examples of such         processing steps are: the network entity 200/410 recognizes that         parts of the received information are the association         information 201/202; based on the recognized parts, the network         entity 200/410 may extract the association information 201/202;         based on the extracted association information 201/202, the         network entity 200/410 my identify the dataset key related to         the extracted association information 201/202; based on the         identified dataset key, the network entity 200/410 may be able         to add, concatenate, group the obtained association information         201/202 from another entity, the network entity 200/410 may         store such concatenated, grouped association information         201/202.

One issue that can further be considered by the Analytics Function 200 is how the Analytic Function 200 actually executes the generation (and/or update) of analytics information 203 based on the association information 201/202. There are different possibilities to execute such generation (and/or update) of analytics information 203 based on the association information 201/202, which apply to all the operation modes 1-3. For instance, one or more of the following alternatives could be used by Analytics Function 200:

-   -   The Analytics Function 200 can be configured to trigger and/or         execute updates on the generation of analytics information 203,         whenever a new and/or a change in the obtained association         information 201/202 happens.     -   The Analytics Function 200 can be configured to trigger and/or         execute updates in the analytics generation periodically.         Therefore, all changes to the association information 201/202         obtained by the Analytics Function 200 will be queued to be used         only when the cycle of new generation (and/or update) of         analytics is due.     -   The Analytics Function 200 can be configured with a queue that         stores the changes in the association information 201/202 over a         period of time, either when the queue is full and/or the period         of time is approaching, the Analytics Function 200 triggers         and/or executes the generation and/or update of the analytics         information 203.     -   The Analytics Function 200 can be configured with different         levels of urgency for triggering generation and/or update of         analytics information 203 based on association information         201/202. For instance, changes in specific association         information 201/202 may immediately trigger and/or execute the         generation and/or update of analytics information 203 based on         the changed association information 201/202, while regarding         other association information 201/202 the Analytics Function 200         can work using the queue scheme described before.     -   The Analytics Function 200 can trigger and/or perform the         generation of analytics information 203 based on the association         information 201/202 when the Analytics Function 200 receives a         request and/or subscription to an analytics information 203         (e.g., Analytics ID as defined in TS 23.288) that requires the         Analytics Function 200 to identify which are the 5GS entities         and their properties (i.e., network slice association         information and/or the user plane association information) to         determine the entities to collect and/or use the data for         analytics calculation (i.e., generation).

It is also possible that the Analytics Function 200 uses a combination of any two of the operation modes 1-3 to obtain the association information 201/202. For instance:

-   -   The Analytics Function 200 may use operation mode 3 for         obtaining the UPA information 202 and use operation mode 1 for         obtaining the NSA information 201; or     -   The Analytics Function 200 may use operation mode 3 for         obtaining the UPA information 202 and use operation mode 2 for         obtaining the NSA information 201.

In the following, more exemplary embodiments for the network entities according to embodiments of the disclosure (see FIG. 2-FIG. 5) are described based on a 5G mobile network following the architecture defined in 3GPP TS 23.501. Different alternatives of embodiments are possible, even within the 5GS.

The table below gives an overview of possible mappings among network entities according to embodiments of this disclosure, and how they could be realized by 5G entities. The table is not exhaustive, and further combinations of extensions in 5GS entities are possible.

Applicable Operation Mapping to Network Entity Modes 5GS Entity Possible extensions of 5GS Entity Network Entity 200 All NWDAF Request and receive the association (FIG. 2) information Generate analytics using the association information, determine the association information, e.g., UP NFs, TAs, Cells, network slices - of the raw data (collected or to be triggered to be collected) to be used for generating the analytics information. Network Entity 310 2 and 3 SMF for Extension of list of events exposed by (FIG. 3) exposing UPA SMF e.g. via Nsmf_EventExposure information (Operation Mode 2; and Option 2 of Operation Mode 3) SMF for Extension of the UE Context information exposing UPA that SMF registers in UDM e.g. via information in Nudm_UECM_Registration to include in UE context the UPA information (Option 3 of registration Operation Mode 3) AMF for NSA Extension of list of events exposed by information AMF via e.g. Namf_EventExposure (Operation Mode 2; and Option 2 of Operation Mode 3) AMF for Extension of the UE Context information exposing NSA that AMF registers at UDM via e.g. information in Nudm_UECM_Registration to include in UE context the NSA information (Option 3 of registration Operation Mode 3) NSSF for NSA New event exposure service to be information defined for NSSF to expose the network slice association information (Operation Mode 2; and Option 2 of Operation Mode 3) Network Entity 410 3 UDM Extension of the UE Context information (FIG. 4) that SMF/AMF registers in UDM via e.g. Nudm_UECM_Registration to include in the association information Extension of e.g. Nudm_UECM_Get to include the association information Extension of UDM e.g. Nudm_EventExposure services to include events about association information. Definition of a new service in UDM allowing the exposure of association information to consumers of such service Create a new UDM type of data (extending tables in Clause 5.2.3 in TS 23.502) related to association information to enable consumers to directly collect such data without having to request data using UE Context related services. UDR Create a new UDM type of data (extending tables in Clause 5.2.3 in TS 23.502) related to association information to enable consumers of UDR to store the information and to query such data without having to request data using UEs as the dataset key.

From the possible implementations listed in the above table, the following are selected for description in detail:

-   -   Embodiment 1—operation mode 1 with the following entities         involved: network entity 510 of FIG. 5 (management plane entity;         e.g. OAM), and network entity 200 of FIG. 2 (Analytics Function;         e.g. NWDAF).     -   Embodiment 2—operation mode 2 with the following entities         involved: network entity 310 of FIG. 3 (NFs enhanced with         association information; e.g. SMF, AMF) and network entity 200         of FIG. 2 (analytics function; e.g. NWDAF).         -   SMF and AMF considering the extensions on the Event             Exposure; and one variant with NSSF exposing the network             slice association information instead of AMF         -   NWDAF directly subscribing to the events exposed by SMF,             AMF.     -   Embodiment 3—operation mode 3 with the following entities         involved: determined network entity 410 of FIG. 4 (NF enhanced         with centralization of association information) and network         entity 200 of FIG. 2 (Analytics function; e.g. NWDAF).         -   SMF exposes the UP association information with enhanced UDM             UE Context registration         -   NSSF is enhanced with a new service for event exposure to             provide the NSA information 201.         -   UDM is enhanced with extended UE Context registration, new             data type to reflect the association information 201/202;             and a new service to expose association information 201/202.         -   NWDAF 200 consuming the new service from UDM to determine             association information 201/202.

FIG. 7 illustrates the embodiment 1 of operation mode 1, and is based on OAM invoking NWDAF services to configure association information

In this embodiment 1, the network entity 200 is exemplarily the NWDAF, which is extended with a new service called Nnwdaf Associationlnfo that allows other entities, such as a management entity 510 (here exemplarily OAM) or a network entity 310 (here exemplarily the NSSF), to provide the association information 201/202. The new service can expose the following operations:

-   -   Create: may allow the creation of association information         201/202 at the NWDAF 200. The input parameters of this operation         may include the fields of the association information 201/202 to         be stored at the NWDAF 200, and the output of this operation may         be an identifier to the stored association information 201/202.     -   Update: may allow a consumer of this service operation to change         the content of a stored association information 201/202. The         input parameters may be the identifier of the stored association         information 201/202, and the association information 201/202         with the modified fields and or values.     -   Delete: may allow a consumer of this service operation to delete         the content of a stored association information 201/202. The         input parameters may be the identifier of the stored association         information 201/202 to be removed.

In FIG. 7, the following steps are shown:

-   -   1a. The NSSF 310 or OAM 510 invokes the Nnwdaf_AssociationInfo         service operation from the NWDAF 200 with the appropriate         parameters.     -   1b. The NWDAF 200 processes the received information from the         NSSF 310 or OAM 510.     -   2. The NWDAF 200 generates analytics information 203 based on         the received association information 201/202. Based on the         vendor strategy, the NWDAF 200 may trigger the generation and/or         update of analytics information 203 based on the received         association information 201/202. For instance, the NWDAF 200 can         use a queue system to trigger the analytics generation and/or         update based on the received association information 201/202.

FIG. 8 illustrates the embodiment 2 of operation mode 2, and is based on the NWDAF using Extensions to Existing Event Exposure Services. In this embodiment 2, the proposed entities and concepts are mapped as follows:

-   -   The network entity 200 is exemplarily the NWDAF for implementing         the Analytics Function.     -   The NSSF, AMF and SMF are exemplarily network entities 310         implementing NFs enhanced with association information.     -   The AMF is the NF 310 enhanced with association information that         detects the NSA information 201, which comprises at least one         of:         -   List of TA(s), for each TA, list of Cells identification             with their related Access Types (e.g., eNB, or 5G NR, or             non-3GPP, etc.), list of allowed S-NSSAI(s) and/or list of             allowed NSI(s) that the AMF instance can support         -   List of TA(s), for each TA, list of Cells identification             with their related Access Types, list of restricted             S-NSSAI(s) and/or restricted NSI(s) per PLMN for such AMF             instance.     -   The NSSF is the NF 310 enhanced with association information         that detects the NSA information 201, which comprises at least         one of:         -   A list of TA(s), for each TA a list of Cells identification             with their associated Access Type, list of allowed             S-NSSAI(s) and/or list of allowed NSI(s)         -   A list of TA, for each TA a list of Cells identification             with their Access Type, list of restricted S-NSSAI(s) and/or             restricted NSI(s) per PLMN     -   The SMF is the NF 310 enhanced with association information that         detect the UPA information 202, which comprises:         -   List of UEs (e.g., identified by SUPI), for each UE a list             of the UE PDU sessions identification (UL and/or DL), for             each UE PDU session identification a list of UPFs and their             N3 and N9 interfaces, or         -   List of UEs (e.g., identified by SUPI), for each UE a list             of UPFs transmitting the UE data traffic, for each UPF the             list of N3 and/or N9 and/or N6 interfaces, or         -   List of UEs (e.g., identified by User identity), for each UE             list of NEF ID transmitting UL and/or DL for such UE.

In FIG. 8, the following steps are shown:

-   -   1. The NWDAF 200 may obtain the NSA information 201 according to         different possible alternatives. Step 1a is related to the first         alternative, where the NSA information 201 is obtained via         interaction with AMF 310, while step 1b is related to the second         alternative where the NSA information 201 is obtained from the         NSSF 310.     -   1a. (Option 1) The NWDAF 200 may invoke the         Namf_EventExposure_Subscribe request method from the AMF 310,         and subscribe to receive a new type of event exposed by the AMF         310 called NSA event. In the subscription, the NWDAF 200 may         indicate if the NSA information 201 is focused on a specific TA         or to any TA supported by the AMF instance. The new NSA event         contains the information about the requested TA and/or list of         TA(s) by the NWDAF 200, for each TA, list of Cells         identification with their related Access Types (e.g., eNB, or 5G         NR, or non-3GPP, etc.), list of allowed S-NSSAI(s) and/or list         of allowed NSI(s) that the AMF 310 instance can support. If any         changes in the information related to the TA for such AMF 310         changes (e.g., a certain S-NSSAI becomes restricted to the AMF),         the AMF 310 should notify the NWDAF 200 with the updated NSA.         The AMF 310 may be capable of storing and maintaining the NSA         event due to its interaction with the NSSF 310 via the         Nnssf_NSSAIAvailability service to acquire the mapping between         TAs and allowed x restricted S-NSSAIs and/or NSIs that it (the         AMF 310) can handle, and the AMF 310 may combine such         information from the NSSF 310 with the its own configured         information about the mapping of cells related to TAs. Combining         these 2 information, the AMF 310 may be able to provide the NSA         event to the NWDAF 200.     -   1b. (Option 2) The NWDAF 200 may invoke a new defined         Nnssf_EventExposure_Subscribe request method from the NSSF 310         and subscribe to receive a new type of event exposed by the SMF         310 called NSA event. In the subscription, the NWDAF 200         indicates if the NSA information 201 related to the NSA Event         (i.e., the Event Filter Information for the NSA event) is         focused on specific TA(s) or any TA supported, a list of AMFs         310 or any AMF 310; a list of cells or any cell, a list of         S-NSSAIs and/or NSIs or any S-NSSAIs and/or NSIs. The new NSA         event may contains the information about the requested TA and/or         list of TA(s) by NWDAF, for each TA, list of Cells         identification with their related Access Types (e.g., eNB, or 5G         NR, or non-3GPP, etc.), list of allowed S-NSSAI(s) and/or list         of allowed NSI(s) that the AMF 310 instance can support. If any         changes in the information related to NSA event requested         changes (e.g., a certain S-NSSAI becomes restricted to a certain         AMF), the NSSF 310 should notify the NWDAF 200 with the updated         NSA.

The NSSF 310 may be capable of storing and maintaining the NSA event due to its interaction with the AMF 310 via the Nnssf_NSSAIAvailability service to acquire the mapping between TAs and cells related to an AMF instance (i.e., that can be handled/served by an AMF instance). The NSSF 310 may combine such information obtained from the AMF 310 with its own configured information about the mapping of TA(s) related to restricted and/or allowed S-NSSAIs and/or NSIs. Combining these 2 information, the NSSF 310 may be able to provide the NSA event to the NWDAF 200.

-   -   2. The NWDAF may obtain the UPA information 200 according to         different alternatives. The NWDAF 200 may invoke the Nsmf         EventExposure Subscribe request method from SMF 310 and         subscribe to receive a new type of event exposed by SMF called         UPA event. The UPA event may have two parts: the event filter         information, which defines the parameter types and values         related to a required UPA information to be compared against the         actual UPA information ; and the event output data, which is the         actual UPA information 200 to be provided by the SMF 310 based         on the requested UPA event with indicated event filter         information.         -   In the subscription, the NWDAF 200 may indicate the event             filter information that defines the focus of the UPA             information 202 to be provided in the UPA event to NWDAF 200             by SMF 310. The event filter information of the request UPA             event contains the information about the requested UE,             and/or any UE, and/or list of UEs, and/or group of UEs,             and/or DNN and/or DNAI information (that allows SMF to             determine which N6 interfaces are relevant for the UPA             Event, and therefore N3, N9, and UPF instances), and/or             S-NSSAI(s) and/or NSI(s).         -   The SMF 310 may provide to NWDAF 200 the UPA information 202             matching the requested Event Filter information. If any             change happens in the mapping of the CN properties             associated with the transmitted data traffic to and/or from             UEs (e.g., the target elements of UPA information); SMF 310             will trigger the notification of the changed value to NWDAF             200. For instance, if a modification of a PDU session (as             defined in Clause 4.3.3 in 3GPP TS 23.502) related to a UE             and/or DNN and/or S-NSSAI (e.g., the target elements of UPA             information) included in the Event Filter Information of the             NWDAF 200 subscription to UPA event at SMF 310, then SMF 310             will provide to NWDAF 200 an update in the subscribed UPA             event, containing the changes in the UPA information 202.             For instance, if a new UPF NF instances has been selected             for transmitting the data traffic of a UE (included in the             event filter information), SMF will update the UPA             information 202 mapping the new UPF NF instance ID as             another CN property related to the data traffic of such UE,             and provide to NWDAF 200, via notification, the update UPA             information 202.     -   3. The NWDAF 200, upon receiving the association information         201/202 may update its internal data structures data keep such         association information 201/202. In the case of this embodiment,         the obtained information is a data structured already organized         as the NSA 201 and/or UPA information 201, therefore the         processing (e.g., aggregation) in this case is just to store the         received information according with the index used for NSA         and/or UP information 201/202. For instance, NWDAF 200 can have         a data structure for NSA information 201 indexed per TA, where         for each TA NWDAF maintains a list of cell IDs, allowed S-NSSAIs         and/or NSIs, list of restricted S-NSSAIs and/or NSIs; and         further for each allowed and/or restricted S-NSSAI and/or NSI,         NWDAF keeps a list of related AMFs.     -   4. Based on the obtained association information, NWDAF 200         generates analytics information 203. The actual process of         analytics generation involves NWDAF 200 triggering data         collection (if data is not available) of raw data (e.g.,         throughput of a Cell, bitrate of PDU session ID in an UPF))         and/or use of such data and/or previously collected raw data to         perform calculations and/or applies statistical analysis, and/or         applies ML/AI techniques (such as regression models, neural         networks, etc.) to produce an analytics information 203.         -   In order to trigger raw data collection from sources of data             collection and/or use available collected raw data from             sources of data collection, NWDAF 200 has to determine the             association information 201/202 that matches the requested             analytics information 203 (e.g., target of analytics             information and/or analytics filter information). Such             requested analytics information 203 can be related to             specific UE(s) and/or groups of UEs, and/or an area of             interest (e.g., list of TA(s), Cell(s)). For instance, there             exist analytics information 203 that have as filters for             subscription a specific geographical area, such as analytics             IDs: Service Experience (3GPP TS 23.288 in Clause 6.4) and             User data congestion in a geographic area (3GPP TS 23.288 in             Clause 6.8.1). In this case, NWDAF 200 has to identify the             network slice association information 201/202 for the tuple             “(TAs, Cells ID, network slices and/or network slices             instances)” in order to properly identify the Cell IDs and             or TA(s) that need to be used in the request for performance             information, when NWDAF 200 interacts with OAM to collect             such data for the specific area of interest. Therefore, in             this example NWDAF 200 generates analytics information based             on network slice association information, otherwise NWDAF             200 would not be able to determine the Cell IDs and/or TA(s)             that are data sources for the requested analytics             information 203.

FIG. 9 illustrates the embodiment 3 of operation mode 3, and is based on NWDAF using UDM Existing Services for Collecting Association Information and New service for exposing Association Information to NWDAF:

In this embodiment 3, the proposed entities and concepts are mapped as follows:

-   -   The network entity 200 is exemplarily the NWDAF 200 for         implementing the Analytics Function.     -   The AMF and SMF are exemplarily network entities 300         implementing NFs enhanced with association information.     -   The UDM is exemplarily the network entity 410 implementing an NF         enhanced with centralization of association information (i.e., a         determined NF 410).     -   The AMF 310 is the NF enhanced with association information that         detects the NSA information 202, which comprises at least one         of:         -   List of TA(s), for each TA, list of Cells identification             with their related Access Types (e.g., eNB, or 5G NR, or             non-3GPP, etc.), list of allowed S-NSSAI(s) and/or list of             allowed NSI(s) that the AMF instance can support.         -   List of TA(s), for each TA, list of Cells identification             with their related Access Types, list of restricted             S-NSSAI(s) and/or restricted NSI(s) per PLMN for such AMF             instance.     -   The SMF 310 is the NF enhanced with association information that         detects the UPA information 202, which comprises at least one         of:         -   List of UEs (e.g., identified by SUPI), for each UE a list             of the UE PDU sessions identification (UL and/or DL), for             each UE PDU session identification a list of UPFs and their             N3 and N9 interfaces, or         -   List of UEs (e.g., identified by SUPI), for each UE a list             of UPFs transmitting the UE data traffic, for each UPF the             list of N3 and/or N9 and/or N6 interfaces         -   List of UEs (e.g., identified by User identity), for each UE             list of NEF ID transmitting UL and/or DL for such UE.     -   The UDM 410 is the NF enhanced with centralization of         association information, and is extended with new data         structures to store and maintain the NSA information 201 and/or         the UPA information 202.         -   The data structure for NSA information 201 can be indexed             per:             -   S-NSSAI and/or NSI, where for each S-NSSAI and/or NSI,                 there is a list of TAs, for each TA, there is a list of                 related Cell IDs, and allowed AMFs, and restricted AMFs,                 or             -   TA, where for each TA, there is a list of cells, a list                 of S-NSSAIs and/or NSI, for each S-NSSAI and/or NSI a                 list of allowed AMFs and a list of restricted AMFs.         -   The data structure for UPA information 202 can be indexes in             different ways, as for example per:             -   UE identification (e.g., SUPI) and/or UE group                 identification (e.g., Internal group identifier), where                 for each UE and/or UE group, there is a list of PDU                 sessions, for each PDU session, there is a the DNN                 and/or DNAI related to the PDU session, and a list of NF                 instance identification related to the transmission of                 data traffic of a PDU session, if the NF instance is a                 UP NF type, such as UPF NF Type, for each UPF NF ID                 there is a list of N3 and/or N9, and/or N6 interfaces                 associated with such UPF NF ID;             -   DN (i.e., DNN and/or DNAI), for each data network, there                 is a list of UE identification (e.g., SUPI) and/or UE                 group identification (e.g., Internal group identifier),                 where for each UE and/or UE group, there is a list of                 PDU sessions, for each PDU session, there is a list of                 NF instance identification related to the transmission                 of data traffic of a PDU session, if the NF instance is                 a UP NF type, such as UPF NF Type, for each UPF NF ID                 there is a list of N3 and/or N9, and/or N6 interfaces                 associated with such UPF NF ID;

In FIG. 9, the following steps are shown:

The UDM 410 may centralize the association information (e.g., the determined NF) 201/202 by obtaining from multiple NFs 310 the NSA and/or UPA information 201/202. In this embodiment, the option is considered, in which the NSA and/or UPA information 201/202 are obtained by UDM 410 via extension of existing services of UDM for acquiring UE context information from both AMF 310 and SMF 310. The UDM services for managing UE Context information are extended with the NSA 201 and UPA information 202. Therefore, whenever SMF 310 and AMF 310 update and/or create and/or deregister UE context information, the UDM 410 extracts (e.g., process, aggregates) from the enhanced UE Context information the NSA and the UPA information 201/202. In this case, UDM 410 obtain NSA and UPA information 201/202 from AMF 310 and SMF 310 upon changes in the UE context related for instance to UE changing its location in the network (e.g., change of TA, or cell ID), or UE being services by a different AMF 310; or establishment or modification of PDU sessions for an UE; or change on SMF 310 serving UEs; or change of UPF serving the PDU sessions (which is a new type of change we introduce with this disclosure).

-   -   1. AMF 310 invokes Nudm_UECM_Deregistration upon the need to         remove from UDM 410 the information that such AMF 310 instance         is serving a certain UE in the network because the S-NSSAI         associated with the TA of the UE has changed from allowed to         restricted. In this case, the Nudm_UECM_Deregistration service         operation is extended with the NSA information 310, which may         comprise at least one of the following input parameters: a list         S-NSSAIs, for each S-NSSAI the list of TA(s) for which the TA         status has changed (i.e., TA has become restricted/unrestricted         in the S-NSSAI). Another example of extensions is in         Nudm_UECM_Registration service operation. In this case, AMF 310         invokes Nudm_UECM_Registration upon the need to include the         information of a new NF in a TA serving an UE, which means that         there is a change in NFs related to TA and S- NSSAIs from UDM         410 perspective. In this case, the input parameters of         Nudm_UECM_Registration service operation are extended to include         NSA information 210, which may comprise at least one of: when         the NF type is AMF 310, list of TA, for each S-NSSAIs allowed         for the UE under registration; and for each TA a list of Cell         IDs.     -   2. SMF 310 invokes Nudm_UECM_Registration service operation upon         the need to register a new PDU session being established for the         UE, which means that there is a change in the overall mapping of         core network properties and data traffic to/from UEs. For the NF         type SMF 310, the input parameters are extended to reflect the         UPA information 202, which may comprise at least one of: list of         NF instances ID related to the transmission of the UEs data         traffic, and for each NF instance a list of interfaces and/or         reference points transmitting data traffic to and/or from the UE         indicated in the Nudm_UECM_Registration service operation.         -   SMF 310 can also invoke the Nudm_UECM_Update service             operation upon changes in the mapping of NF instances and/or             interfaces and/or reference points being used for the             transmission of the UE data traffic. In this case, the input             parameters of Nudm_UECM_Update service operation are             extended to include in the case of SMF 310 Type the UPA             information 202 comprising of at least one of: the list of             UEs that have some change in their sessions, for each UE the             list of PDU sessions that changes, for each PDU session, the             list of NF instance IDs transmitting the data traffic with             the status (included, removed, updated), and for each NF             instances IDs with status updated, the list of interfaces             and/or reference points transmitting data traffic to and/or             from the UE with their respective status (removed,             included).     -   3. UDM 410 upon receiving the NSA and/or UPA information         201/202, respectively from AMF 310 and SMF 310, extracts from         the input parameters received in service operation from the         interface Nudm_UECM the related NSA and UPA information 201/202.         From the received information via Nudm_UECM service interface,         UDM 410 is also capable to identify that the received NSA and/or         UPA information 201/202 is associated with the indexes the UDM         410 uses for controlling the data structures for NSA and/or UPA         information 201/202. By extracting the indexes and NSA and/or         UPA information 201/02 from the input parameters from Nudm_UECM         service operations, UDM 410 can assemble, compose (e.g.,         aggregate) the NSA and/or UPA information 201/202 for the value         of the index and update existing entry or create a new entry in         the data structure of the NSA and/or UPA information 201/202.     -   4. UDM 410 stores the extracted NSA and/or UPA information.     -   5. UDM 410 may be enhanced with a new service         Nudm_AssociationInformation, wherein one of the possible         embodiments for UDM 410 providing NSA and/or UPA information         201/202 to NWDAF 200 is as follows.         -   NWDAF 200 invokes the Nudm_AssociationInformation_Get             request service operation from UDM 410 (i.e., determined             NF). NWDAF 200 may query NRF to identify the proper UDM             instance to invoke or it can be configured with the proper             UDM instance. NWDAF 200 includes as input parameters the             following information: the type of association information             201/202 required (i.e., NSI and/or UPA), the association             filter information for the respective type of the             association information 201/202 required (i.e., the request             for NSA and/or UPA information 201/202). The association             filter information can be any of the fields of the NSA             and/or UPA information 201/202, and it includes the values             for such fields.         -   For instance, NWDAF 200 may include in invocation of             Nudm_AssociationInformation_Get at least one of the             following association filter information:         -   For UPA information 202, the association filter information             can be at least one of: list of UE(s), or indication of “any             UE”, and/or groups of UEs, and/or DNN and/or DNAI             information, and/or S-NSSAI(s) and/or NSI(s).         -   For NSA information 201, the association filter information             can be at least one of: a list of AMFs 310 or any AMF 310; a             list of cells or any cell, a list of S-NSSAIs and/or NSIs or             any S-NSSAIs and/or NSIs.         -   This association filter information indicated by NWDAF 200             in the request for NSA and/or UPA information 201/202 to UDM             410, will be used by UDM 410 to search its internal NSA             and/or UPA information 201/202 data structure, in order to             retrieve (i.e., select) the entries that match the fields             and values indicated in the association filter information.         -   The entries of the NSA and/or UPA information 201/202 data             structure are included in Nudm_AssociationInformation_Get             response that UDM 410 sends, i.e., provides to NWDAF. The             possible output parameters are at least one of:         -   When NSA information 201 is provided: List of S-NSSAI and/or             NSI, where for each S-NSSAI and/or NSI, there is a list of             TAs, for each TA, there is a list of related Cell IDs, and             allowed AMFs, and restricted AMFs         -   When UPA information 202 is provided: list of UE             identification (e.g., SUPI) or UE group identification             (e.g., Internal group identifier), where for each UE or UE             group identification, there is a list of PDU sessions, for             each PDU session, there is a the DNN and/or DNAI related to             the PDU session, and a list of NF instance identification             related to the transmission of data traffic of a PDU             session, if the NF instance is a UP NF type, such as UPF NF             Type, for each UPF NF ID there is a list of N3 and/or N9,             and/or N6 interfaces associated with such UPF NF ID.

Notably, the same type of embodiment of a service following the request-response method defined in the Nudm_AssociationInformation_Get, could be a possible embodiment for extensions of AMF 310 (or NSSF 310) and SMF 310 in the operation Mode 2.

FIG. 10 shows a method 1000 according to an embodiment of the disclosure. The method 1000 is usable for generating analytics. The method 1000 may be performed by the network entity 200 of FIG. 2.

The method 1000 comprises a step 1001 of obtaining NSA information 201 and/or UPA information 202 from one or more network entities 210, 310, 410, 510 (see e.g. FIG. 2-FIG. 5). Further, the method 1000 includes a step 1002 of providing analytics information 203, wherein the analytics information 203 is based on the obtained NSA information 201 and/or UPA information 202.

FIG. 11 shows three methodsaccording to embodiments of the disclosure.

In (a), a method 1100 for supporting analytics generation, e.g. performed by the network entity 200 of FIG. 2, is shown. The method 1100 may be performed by the network entity 310 of FIG. 3. The method 1100 comprises a step of providing NSA information 201 and/or UPA information 202 to another network entity 300, 400 (see FIG. 3 or FIG. 4), in response to a request 301, 401 received from and/or according to a subscription from the other network entity 300, 400. Alternatively, or in addition, the method 1100 includes a step of providing NSA information 201 and/or UPA information 202 to another network entity 300, 400, upon changes in one or more target elements related to the NSA information 201 and/or UPA information 202, the one or more target elements being related to the network entity 200 or 310. The other network entity 300, 400 may be the network entity of FIG. 2.

In (b) a method 1101 for supporting analytics generation, e.g. performed by the network entity 200 of FIG. 2, is shown. The method 1101 may be performed by the network entity 410 of FIG. 4. The method 1101 comprises a step of obtaining NSA information 201 a and/or UPA information 202 a from another network entity 420 (see e.g. FIG. 4), in response to a first request 411 sent to and/or according to a first subscription to the other network entity 420. Alternatively, or in addition, the method 1100 comprises a step of obtaining NSA information 201 b and/or UPA information 202 b from another network entity 420, upon changes in one or more target elements related to the NSA information 201 and/or UPA information 202, the one or more target elements being related to the other network entity 420.

In (c) a method 1102 for supporting analytics generation, e.g. as performed by the network entity 200 of FIG. 2, is shown. The method 1102 may be performed by the network entity 510 of FIG. 5. The method comprises a step of configuring a network entity 500 with NSA information 201 and/or UPA information 202, wherein the other network entity 500 is, in particular, a Network Data Analytics Function, NWDAF, and/or a Unified Data Management, UDM, and/or a Unified Data Repository, UDR, e.g. is the network entity 200 of FIG. 2.

The present disclosure has been described in conjunction with various embodiments as examples as well as implementations. However, other variations can be understood and effected by those persons skilled in the art and practicing the claimed invention, from the studies of the drawings, this disclosure and the independent claims. In the claims as well as in the description the word “comprising” does not exclude other elements or steps and the indefinite article “a” or “an” does not exclude a plurality. A single element or other unit may fulfill the functions of several entities or items recited in the claims. The mere fact that certain measures are recited in the mutual different dependent claims does not indicate that a combination of these measures cannot be used in an advantageous implementation. 

1. A network entity for analytics generation, the network entity comprising processing circuitry being configured to: obtain network slice association (NSA), information or user plane association (UPA), information from one or more other network entities, the NSA information indicating a relation between an access network property and a core network property, and the UPA information indicating a transmitting network entity, of the other network entities, configured to transmit data traffic to or from a user equipment in the network; and provide analytics information, the analytics information being based on the obtained NSA information or the obtained UPA information.
 2. The network entity according to claim 1, wherein the processing circuitry is further configured to: obtain the NSA information or the UPA information by configuration from a management plane entity.
 3. The network entity according to claim 1, wherein the processing circuitry is further configured to: send a request or subscribe to one or more network functions (NFs); and obtain the NSA information or the UPA information from the one or more NFs, in response to the request or according to the subscription.
 4. The network entity according to claim 3, wherein: the request or the subscription respectively comprises a request or subscription for the NSA information or the UPA information.
 5. The network entity according to claim 1, wherein the processing circuitry is further configured to: send a plurality of requests or subscribes to a plurality of network functions (NFs); obtain the NSA information or the UPA information from the plurality of NFs, in response to the plurality of requests or according to the subscriptions; aggregate the obtained NSA information or the obtained UPA information; and provide the analytics information, the analytics information being based on the aggregated NSA information or the aggregated UPA information.
 6. The network entity according to claim 1, wherein the processing circuitry is further configured to: send a request or subscribe to a determined network function (NF); obtain the NSA information or the UPA information from the determined NF, in response to the request or according to the subscription; and provide the analytics information, the analytics information being based on the obtained NSA information or the obtained UPA information.
 7. The network entity according to claim 1, wherein: the network entity is a control plane entity comprising a network data analytics function (NWDAF).
 8. A network entity for supporting analytics generation, the network entity comprising processing circuitry being configured to: provide network slice association (NSA), information or user plane association (UPA), information to another network entity, in response to a request received from or according to a subscription from the other network entity, the NSA information indicating a relation between an access network property and a core network property, and the UPA information indicating the other network entity is configured to transmit data traffic to or from a user equipment in the network; or provide the NSA information or the UPA information to another network entity, upon changes in one or more target elements related to the NSA information or the UPA information, the one or more target elements being related to the network entity.
 9. The network entity according to claim 8, wherein: the network entity is a control plane network function (NF) comprising a session management function (SMF), an access and mobility management function (AMF), a network slice selection function (NSSF), a network exposure function (NEF), an application function (AF), or a network repository function (NRF).
 10. A network entity for supporting analytics generation, the network entity comprising processing circuitry being configured to: obtain network slice association (NSA) information or user plane association (UPA) information from another network entity in response to a first request sent to or according to a first subscription to the other network entity; the NSA information indicating a relation between an access network property and a core network property, and the UPA information indicating that the network entity is configured to transmit data traffic to or from a user equipment in the network; or obtain the NSA information or the UPA information from the other network entity, upon changes in one or more target elements related to the NSA information or the UPA information, the one or more target elements being related to the other network entity.
 11. The network entity according to claim 10, wherein the processing circuitry is further configured to: obtain a second request or a second subscription for NSA information or UPA information, from a further network entity; and provide the obtained NSA information, or the obtained UPA information, aggregated NSA information, or aggregated UPA information to the further network entity in response to the second request or according to the second subscription.
 12. The network entity according to claim 10, wherein the processing circuitry is configured to: aggregate the obtained NSA information or the obtained UPA information, or store the obtained NSA information or the obtained UPA information.
 13. The network entity according to claim 10, wherein: the network entity is a control plane entity comprising a unified data management (UDM), a unified data repository (UDR), or a network data analytics function (NWDAF).
 14. A network entity configured as a management plane entity for supporting analytics generation, the network entity comprising processing circuitry being configured to: configure another network entity with network slice association (NSA) information or user plane association (UPA) information, wherein the other network entity is a network data analytics function (NWDAF), a unified data management (UDM), or a unified data repository (UDR), and wherein the NSA information indicates a relation between an access network property and a core network property, and the UPA information indicates the other network entity is configured to transmit data traffic to or from a user equipment in the network.
 15. The network entity according to claim 1, wherein the NSA information comprises at least one of: a cell related to a tracking area (TA), an access type, one or more allowed single network slice selection assistance information (S-NSSAIs) or allowed network slice instances (NSIs), one or more restricted S-NSSAIs or restricted NSI(s), one or more network functions (NFs), or one or more allowed S-NSSAI(s) or allowed NSI(s) per public land mobile network (PLMN) for each related NF; a cell related to the TA, the access type, the one or more allowed S-NSSAIs, the one or more allowed NSIs, one or more of the restricted S-NSSAIs or the restricted NSIs, one or more of the NFs, one or more of the restricted S-NSSAI(s) or the restricted NSI(s) per PLMN for each of the related NF; a TA related to a list of cells, a supported access type, one or more of the allowed S-NSSAI(s) or the allowed NSI(s), one or more of the NFs, or one or more of the allowed S-NSSAI(s) or the allowed NSI(s) for each related NF; the TA related to the list of cells, the supported access type, one or more of the restricted S-NSSAI(s) or the restricted NSI(s) per PLMN, one or more of the NFs, one or more of the restricted S-NSSAI(s) or the restricted NSI(s) per PLMN for each of the related NF; a NF related to a TA, for the TA, one or more related cells, one or more related access types, one or more of the related allowed S-NSSAI(s) or the allowed NSI(s); or the NF related to the TA, for the TA, one or more of the related cells, one or more of the related access types, or one or more of the related restricted S-NSSAI(s) or the restricted NSI(s) per PLMN.
 16. The network entity according to claim 1, wherein the UPA information comprises at least one of: one or more user plane NFs transmitting uplink (UL) or downlink (DL) data traffic related to one or more user equipments (UEs), one or more groups of the UEs, one or more or UE session, one or more data network identification, one or more network slice identification, or one or more application identification; one or more control plane NFs transmitting UL or DL data traffic related to one or more UEs or the one or more groups of UEs or the one or more UE sessions, one or more of the data network identification, one or more of the network slice identification, or one or more of the application identification; one or more user plane interfaces, or links, or reference points, or services, transmitting the UL or DL data traffic related to one or more of the UEs or one or more of the groups of UEs or one or more of the UE sessions, one or more of the data network identification, one or more of the network slice identification, or one or more of the application identification; or one or more control plane interfaces, or links, or reference points, or services, transmitting the UL or DL data traffic related to one or more of the UEs or one or more of the groups of UEs or one or more of the UE sessions, one or more of the data network identification, one or more of the network slice identification-, or one or more of the application identification.
 17. A method for analytics generation, the method comprising: obtaining network slice association (NSA) information or user plane association (UPA) information from one or more network entities, the NSA information indicating a relation between an access network property and a core network property, and the UPA information indicating a network entity of the network entities is configured to transmit data traffic to or from a user equipment in the network; and provide analytics information, the analytics information being based on the obtained NSA information or the obtained UPA information.
 18. A method for supporting analytics generation, the method comprising: providing network slice association (NSA) information or user plane association (UPA) information to another network entity in response to a request received from or according to a subscription from the other network entity, the NSA information indicating a relation between an access network property and a core network property, and the UPA information indicating that the network entity is configured to transmit data traffic to or from a user equipment in the network; or providing the NSA information or the UPA information to another network entity upon changes in one or more target elements related to the NSA information or the UPA information.
 19. A method for supporting analytics generation, the method comprising: obtaining network slice association (NSA) information or user plane association (UPA) information from another network entity in response to a first request sent to or according to a first subscription to the other network entity, the NSA information indicating a relation between an access network property and a core network property, and the UPA information indicating that the other network entity is configured to transmit data traffic to or from a user equipment in the network, or obtaining the NSA information or the UPA information from another network entity upon changes in one or more target elements related to the NSA information or the UPA information, the one or more target elements being related to the other network entity.
 20. A method for supporting analytics generation, the method comprising: configuring another network entity with network slice association (NSA), NSA, information or user plane association (UPA) information, wherein the other network entity is a network data analytics function (NWDAF), a unified data management (UDM), or a unified data repository (UDR), and wherein the NSA information indicates a relation between an access network property and a core network property, and the UPA information indicates the other network entity is configured to transmit data traffic to or from a user equipment in the network.
 21. A non-transitory computer readable medium comprising a program code for performing the method according to claim 1, when executed on a computer. 